1. Field of the Invention
The invention relates to an apparatus and method for image processing, and more particularly to an image processing method/apparatus capable of increasing sharpness in a scaled image.
2. Description of the Related Art
Interpolation is widely used to find unknown pixel values based on the known pixel values. Common interpolation algorithms can be grouped into two categories, adaptive and non-adaptive. Adaptive methods change depending interpolated pixels, while non-adaptive methods treat all pixels equally. Linear interpolation is the most basic form of interpolation. To find an unknown pixel P3 the factors x and (1−x) are used in a weighted average of two known pixels, P1 and P2 as shown by the following formula:P3=P1 by x+P2 by(1−x).
If more pixels adjacent to the unknown pixel P3 are known and included, interpolation of the unknown pixel P3 is more accurate. With the exception of linear interpolation, bilinear interpolation, bicubic interpolation, or higher order interpolation, such as spline and sinc interpolations are also commonly used interpolations for increasing the accuracy of unknown pixels.
FIG. 1 is schematic diagram of an enlarged image by a conventional resizing mechanism. The enlarged image 12 and the bottom image 11 are in different layers, a widely applied technique in display devices. After the image has been enlarged, a blurred edge 13 occurs around the enlarged image 12. Please refer to the enlargement area 14. The pixels 14a and 14e are known pixels, and the pixels 14b, 14c and 14d are determined based on the known pixels, 14a and 14e, and corresponding weighted values. The blurred edge 13 is caused by the interpolated pixels, such as the pixels 14b, 14c and 14d, thus, a low complexity, adaptive and useful image resizing mechanism capable of increasing the sharpness and reducing blur is desirable.